Auto-Conditioned Recurrent Networks for Extended Complex Human Motion Synthesis (bibtex)
by Zimo Li, Yi Zhou, Shuangjiu Xiao, Chong He, Zeng Huang, Hao Li
Abstract:
We present a real-time method for synthesizing highly complex human motions using a novel training regime we call the auto-conditioned Recurrent Neural Network (acRNN).
Reference:
Auto-Conditioned Recurrent Networks for Extended Complex Human Motion Synthesis (Zimo Li, Yi Zhou, Shuangjiu Xiao, Chong He, Zeng Huang, Hao Li), 2017.
Bibtex Entry:
@misc{li2017autoconditioned,
    title = {Auto-Conditioned Recurrent Networks for Extended Complex Human Motion Synthesis},
    author = {Zimo Li and Yi Zhou and Shuangjiu Xiao and Chong He and Zeng Huang and Hao Li},
    year = {2017},
    eprint = {1707.05363},
    archivePrefix = {arXiv},
    primaryClass = {cs.LG},
	abstract = {We present a real-time method for synthesizing highly complex human motions using a novel training regime we call the auto-conditioned Recurrent Neural Network (acRNN).}
	
}
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